KAUST graduates are characterized by the rigor of their Ph.D. programs, the long hours spent in the lab and classroom, juggling professional and personal commitments, achieving a work-life balance and, more recently, the ability to adapt to a global pandemic.
KAUST Distinguished Professor of Statistics Marc Genton has received the Royal Statistical Society’s (RSS) 2023 Barnett Award.
KAUST Ph.D. statistics student Paolo Victor Redondo was selected as a runner-up in the American Statistical Association’s (ASA) Statistics in Imaging Section 2023 Distinguished Student Paper Award Competition
KAUST Associate Professor of Statistics Raphaël Huser has been awarded the Abdel El-Shaarawi Early Investigator (AEEI) Award 2022 from The International Environmetrics Society (TIES), an association of the International Statistical Institute (ISI).
An asymmetric statistical model provides a better fit for imbalanced data with rare "positives," such as longitudinal health datasets.
A deep-learning technique could offer accurate large-scale predictions in the field of geospatial statistics.
The fast-developing science of geospatial statistics offers new insights into diverse health challenges, from cancer hotspots to problems of air pollution and the spread of COVID-19. Three new projects should yield a better understanding of what causes disease in Saudi Arabia and how to fight it.
CEMSE statisticians developed a framework which enables modeling of a range of meteorological and environmental datasets from up to 2 million locations globally.
Esmail Abdul Fattah, a KAUST Ph.D. candidate in statistics, won a poster award in the "junior-BayesComp-ISBA" category at the 30th meeting of the International Society for Bayesian Analysis (ISBA 2022) held from June 26 to July 1 in Montreal, Canada.
CEMSE researchers Matheus Guerrero, Raphaël Huser and Hernando Ombao developed a new approach for analyzing seizures in epilepsy patients by applying extreme value theory to real EEG seizure data.
Xin Gao's team developed an interactive web portal where cancer scientists can interrogate how RNA splicing in noncoding parts of genes fuels the growth of different types of tumors.
A new AI diagnostic tool developed by KAUST scientists allows doctors to visualize lung damage caused by COVID-19 in more detail.
Prof. David Bolin has been selected for the American Statistical Association Section on Statistics and the Environment Early Investigator (ENVR) Award for his outstanding contributions to environmental statistics.
A new study addresses the difficulty in modeling atmospheric turbulence at sub-kilometer resolution, which is challenging due to atmospheric variability, meteorology and changeable terrain such as mountains and cities.
Machine learning techniques can provide accurate forecasting of the spread of viruses during pandemics. Under the supervision of Ying Sun and Fouzi Harrou, Yasminah Alali developed an approach that removes human bias and assumptions, predicting pandemic evolution more accurately.